import numpy as np
import cv2
import multiprocessing
from multiprocessing import Queue
import time
CAMERA_COUNT = 4 # 摄像头个数
url = "rtsp://admin:[email protected]/Streaming/Channels/1" # 外置摄像头地址及密码
url1 = "rtsp://admin:[email protected]/Streaming/Channels/1"
url2 = "rtsp://admin:[email protected]/Streaming/Channels/1"
url3 = "rtsp://admin:[email protected]/Streaming/Channels/1"
# 不同进程不能共享内存,定义队列进行进程通信
q = Queue()
def video_read(id):
camera_id = id
# 使用笔记本自带的摄像头
if camera_id == 0:
cap = cv2.VideoCapture(url)
# 使用外置的摄像头
if camera_id == 1:
cap = cv2.VideoCapture(url1)
# 使用外置的摄像头1
if camera_id == 2:
cap = cv2.VideoCapture(url2)
# 使用外置的摄像头2
if camera_id == 3:
cap = cv2.VideoCapture("1.mp4")
# 获取每一个视频的尺寸
width = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)))
height = (int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
print(width, height)
faceCascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
while (cap.isOpened()):
ret, frame = cap.read()
if ret == True:
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # 将每一帧图片转为灰色以便接下来处理
faces = faceCascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.CASCADE_SCALE_IMAGE
)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
frame = cv2.resize(frame, (640, 480), interpolation=cv2.INTER_CUBIC)
isEmpty = q.empty()
# print(isEmpty)
if isEmpty == True:
# print('队列中无数据!')
# q.put(frame)
time.sleep(0.001)
else:
time.sleep(0.002)
cv2.imshow('videoprossing' + str(id), frame)
key = cv2.waitKey(10)
if int(key) == 113:
break
else:
video_read(id)
cap.release()
cv2.destroyAllWindows()
# ---------------------------------------------------------------------------------
if __name__ == '__main__':
print("主进程开始启动!")
for index in range(CAMERA_COUNT):
print('摄像头的索引号是:', index)
p = multiprocessing.Process(target=video_read, args=(index,))
p.start()
print('程序结束!')
同时从摄像头传入四个视频流并识别视频人脸(使用多线程)
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转载自blog.csdn.net/liaoqingjian/article/details/109110790
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